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Applying generalized linear models

Author: James K Lindsey
Publisher: New York : Springer, ©1997.
Series: Springer texts in statistics.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: James K Lindsey
ISBN: 0387982183 9780387982182
OCLC Number: 36430655
Description: xiii, 256 pages : illustrations ; 24 cm.
Contents: Generalized linear modeling --
Discrete data --
Fitting and comparing probability distributions --
Growth curves --
Time series --
Survival date --
Event histories --
Spatial data --
Normal methods --
Dynamic models --
Appendices: inference; diagnostics.
Series Title: Springer texts in statistics.
Responsibility: James K. Lindsey.
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Abstract:

This book describes how generalised linear modelling procedures can be used in many different fields, without becoming entangled in problems of statistical inference. With many exercises at the end  Read more...

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From a review:TECHNOMETRICS"...one of the best applied statistical books that I have ever read."

 
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<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Agent\/springer<\/a>> # Springer<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:Agent<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Springer<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Series\/springer_texts_in_statistics<\/a>> # Springer texts in statistics.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:PublicationSeries<\/a> ;\u00A0\u00A0\u00A0\nschema:hasPart<\/a> <http:\/\/www.worldcat.org\/oclc\/36430655<\/a>> ; # Applying generalized linear models<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"Springer texts in statistics.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Springer texts in statistics<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Thing\/linear_models<\/a>> # LINEAR MODELS<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"LINEAR MODELS<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Thing\/statistics<\/a>> # STATISTICS<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"STATISTICS<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Topic\/31_73_mathematical_statistics<\/a>> # 31.73 mathematical statistics<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"31.73 mathematical statistics<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Topic\/lineaire_modellen<\/a>> # Lineaire modellen<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Lineaire modellen<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Topic\/linear_models<\/a>> # Linear Models<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Linear Models<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
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<http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Topic\/pesquisa_e_planejamento_estatistica<\/a>> # Pesquisa e planejamento (estatistica)<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Pesquisa e planejamento (estatistica)<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
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<http:\/\/viaf.org\/viaf\/310662060<\/a>> # James K. Lindsey<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Lindsey<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"James K.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"James K. Lindsey<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
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<http:\/\/www.worldcat.org\/title\/-\/oclc\/36430655#PublicationEvent\/new_york_springer_1997<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:PublicationEvent<\/a> ;\u00A0\u00A0\u00A0\nschema:location<\/a> <http:\/\/dbpedia.org\/resource\/New_York_City<\/a>> ; # New York<\/span>\n\u00A0\u00A0\u00A0\nschema:organizer<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/536563#Agent\/springer<\/a>> ; # Springer<\/span>\n\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.worldcat.org\/title\/-\/oclc\/36430655#Review\/1541989673<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Review<\/a> ;\u00A0\u00A0\u00A0\nschema:itemReviewed<\/a> <http:\/\/www.worldcat.org\/oclc\/36430655<\/a>> ; # Applying generalized linear models<\/span>\n\u00A0\u00A0\u00A0\nschema:reviewBody<\/a> \"\"Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis.\" \"This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression, and ANOVA.\"--Jacket.<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Content-negotiable representations<\/p>\n